Machines such as haul trucks, excavators, motor graders, backhoes, water trucks, and other equipment, are utilized at a worksite to accomplish various tasks. With recent developments in the field of automation, automated machines have been developed that may operate at the worksite with minimal manual intervention. Usually, such automated machines utilize a plurality of sensors to determine operating conditions, at the worksite, such as a location of stationary objects, road conditions, and other machines operating at the worksite. Based on the determined operating conditions, the automated machine may operate at the worksite.
Due to dynamic and unpredictable operating conditions at the worksite, some of the sensors mounted on the machine may malfunction. Such malfunctioning sensors are replaced with new sensors by onsite workers/technicians. Before the new sensors are utilized to operate the machine, it may be required to calibrate them. Usually, the machine (with the newly installed sensor) is sent to a service station for the purpose of calibration of the new sensors. This in turn may slow down the work progress at the worksite.
U.S. Pat. No. 9,052,721 ('721 reference) discloses a system and a method for alignment of light detection and ranging (LIDAR) data. The '721 reference discloses a method to align a 3D point cloud, captured by a sensor mounted on the vehicle, with a reference 3D point cloud to avoid false detection of obstacles on the road. Further, the alignment of the two 3D point clouds may be utilized to determine yaw, pitch, and roll of the vehicle. However, the '721 reference is silent on calibration of the sensor mounted on the vehicle.
Accordingly, the system and method of the present disclosure solves one or more problems set forth above and other problems in the art.